A reliability model to predict failure behaviour of overlying strata in groundwater-rich coal mine by Ruirui Li, Xiaowei Hou, Luwang Chen, Yingxin Wang, Fuyou Huang, Lanting Wang

“…In this study, a reliability model with consideration of spatial variability and uncertainty of strength parameters was proposed to predict the failure behaviour of overlying strata during coal mining in groundwater-rich coalfields. …”
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Spatiotemporal patterns and prediction of multi-region house prices via functional mixed effects model by Yilin Chen, Haitao Zheng

Subjects: “…house price prediction…”
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Reduction of Russia’s Energy Exports: Spatial Distribution of Economic Effects by Natalya Gennadievna Dzhurka, Olga Valeryevna Dyomina

“…This paper is devoted to the assessment of the size and spatial distribution of economic effects caused by the introduction of sanctions on the export of Russian fuel and energy resources. …”
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Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network by Xiang Gu, Chao Li, Jie Yang, Jing Wang, Qiwei Huang

“…However, the task still faces challenges in modeling long-term dependencies, complex spatial interactions, and multi-scale feature fusion. …”
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Spatial and Temporal Characteristics of Land Use Changes in the Yellow River Basin from 1990 to 2021 and Future Predictions by Yali Cheng, Yangbo Chen

“…Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. …”
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Spatial interpolation of health and demographic variables: Predicting malaria indicators with and without covariates. by Camille Morlighem, Chibuzor Christopher Nnanatu, Corentin Visée, Atoumane Fall, Catherine Linard

“…Overall, socioeconomic indicators were generally better predicted by covariate-based models (e.g., random forest and Bayesian models), while methods using spatial autocorrelation alone (e.g., thin plate splines) performed better for variables with heterogeneous spatial structure, such as ethnicity and malaria prevention indicators. …”
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Graphormer Boosted: Molecular Property Prediction With Enhanced Graph Spatial and Edge Encodings by Sarah A. Fadlallah, Francesc Serratosa, Carme Julia

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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

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Investigating Durban’s Morphological Dynamics and Spatial Prediction Techniques for Urban Geography Pedagogy by Tolulope Ayodeji Olatoye, Raymond Nkwenti Fru

“…This study highlighted the transformative potential of geospatial analysis and spatial prediction techniques in using the dynamic morphology of Durban Metropolis as a model for fostering innovative, data-driven learning experiences. …”
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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

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A Spatially Informed Machine Learning Method for Predicting Sound Field Uncertainty by Xiangmei Chen, Chao Li, Haibin Wang, Yupeng Tai, Jun Wang, Cyrille Migniot

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Combining habitat selection, behavioural states, and individual variation to predict fish spatial usage near a barrier by Rachel Mawer, Jelger Elings, Stijn P. Bruneel, Ine S. Pauwels, Eliezer Pickholtz, Renanel Pickholtz, Johan Coeck, Peter L.M. Goethals

“…Model results were explored to assess the benefits of including behavioural state and understand state-specific habitat preferences, then cross-validated and used to develop an individual based model to predict fish spatial usage. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Adopt four different noise reduction algorithms for data noise reduction on the raw data of the monitoring points at the intervals of different risk zones, and combine the time series prediction as well as the deep learning prediction method to get the prediction model for environmental risk zoning based on the environmental risk zoning. …”
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Estimating building height using scene classification and spatial geometry by Yonghua Jiang, Jingxin Chang, Yunming Wang, Shaodong Wei, Deren Li

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STVMamba: precipitation nowcasting with spatiotemporal prediction model by Maoyang Zou, Longrui Wen, Yuanyuan Huang, Yuan He, Jingzhong Xiao

“…The Spatial-Temporal Vision Mamba (STVMamba) is proposed, a novel spatiotemporal prediction model specifically designed for precipitation nowcasting. …”
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A multimodal model for protein function prediction by Yu Mao, WenHui Xu, Yue Shun, LongXin Chai, Lei Xue, Yong Yang, Mei Li

“…Protein structure provides richer spatial and functional insights, which can significantly improve prediction accuracy. …”
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Prediction Modeling and Driving Factor Analysis of Spatial Distribution of CO₂ Emissions from Urban Land in the Yangtze River Economic Belt, China by Chao Wang, Jianing Wang, Le Ma, Mingming Jia, Jiaying Chen, Zhenfeng Shao, Nengcheng Chen

“…Based on socioeconomic grid data, such as nighttime lights and the population, this study proposes a spatial prediction method for CO₂ emissions from urban land using a Long Short-Term Memory (LSTM) model with added fully connected layers. …”
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Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism by Zeguo Zhang, Jianchuan Yin

“…Comprehensive discussions with both temporal and spatial perspective, revealing that the proposed model can offer an accurate 2D wind gust prediction along timeline (the PCC equals to 0.98).…”
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Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Gonghe Basin by Hong Jia, Siqi Yang, Lianyou Liu, Hang Li, Zeshi Li, Yixin Chen, Jifu Liu

“…Based on the land use data of the Gonghe Basin from 1990 to 2020, the InVEST model was applied to analyze the spatiotemporal changes in carbon storage, and the PLUS model was used to predict the changes in carbon storage under three different development scenarios in 2030. …”
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Enhancing land use planning through integrating landscape analysis and flood inundation prediction Bekasi City’s in 2030 by Novia Fitriyati, Hadi Susilo Arifin, R. L. Kaswanto, Marimin

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